Data management planning for ESRC researchers

Data management plan

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All ESRC grant applicants generating data during their research have to include a data management plan with their Je-S grant application.

A data management plan helps decide how research data will be managed throughout the research cycle and how best to prepare for data deposit with the UK Data Service. Most research data can be successfully archived and shared for future reuse.

ESRC expects grant holders to consider all issues related to confidentiality, ethics, security and copyright before initiating the research. Any challenges to data sharing (such as copyright or data confidentiality) should be critically considered in a plan, with possible solutions discussed to optimise data sharing.

A data management plan includes the following topics.

1. Assessment of existing data

an explanation of the existing data sources that will be used by the research project, with references

an analysis of the gaps identified between the currently available and required data for the research

Where research grant applicants plan to create new data as part of their ESRC-funded proposal, they must demonstrate that no suitable data are available for re-use. ESRC encourages the re-use of existing data and therefore encourages applicants and grant holders to consider the breadth of data available from various sources before committing to primary data collection.

When using existing data sources, consider copyright and Intellectual Property rights (IPR) of those data and the conditions of their use, to decide whether resulting derived data can be shared.

Data sources that can be consulted are:

Discover UK Data Service, with over 6,000 datasets of key economic, social and historical data spanning many disciplines and themes

Provide information on the data that will be produced or accessed by the research project:

data volume

data type

data quality, formats, standards documentation and metadata

methodologies for data collection and/or processing

source and trustworthiness of third party data

Using standardised and interchangeable data formats ensures the long-term usability of data. Clear and detailed data descriptions and annotation, together with user-friendly accompanying documentation on methods and contextual information, makes data easy to understand and interpret and therefore shareable and with long-lasting usability.

Quality control of data is an integral part of a research process. The procedures for quality assurance that will be carried out on the data collected at the time of data collection, data entry, digitisation and data checking should be described.

Describe the data security and backup procedures that you will adopt to ensure the data and metadata are securely stored during the lifetime of the project. If your data is sensitive (e.g. detailed personal data) you should discuss appropriate security measures which you will be taking. You may need to discuss your institution's policy on backups.

Outline your plans for preparing, organising and documenting data. A crucial part of making data user-friendly, shareable and with long-lasting usability is to ensure they can be understood and interpreted by other users. This requires clear and detailed data description, annotation and contextual information, as well as good-structured and well-organised data files.

Identify any potential obstacles to sharing your data, explain which and the possible measures you can apply to overcome these. State explicitly which data may be difficult to share and why. If ethical issues could cause difficulties in data sharing, explain your strategies for dealing with these issues in the relevant section of the Je-S form, e.g. discussing data sharing with interviewees as part of consent discussions or anonymising data.

The ESRC supports the position that most data can be curated and shared ethically provided researchers pay attention right from the planning stages of research to the following aspects:

when gaining informed consent, include consent for data sharing

where needed, protect participants’ identities by anonymising data

address access restrictions to data in the data management and sharing plan, before commencing research.

7. consent, anonymisation and strategies to enable further re-use of data

Make explicit mention of the planned procedures to handle consent for data sharing for data obtained from human participants, and/or how to anonymise data, to make sure that data can be made available and accessible for future scientific research.

If unsure how issues of confidentiality are to be addressed to facilitate data sharing, please get in touch for advice.

Indicate who within your research team will be responsible for data management, metadata production, dealing with quality issues and the final delivery of data for sharing or archiving. Provide this information within the Staff Duties section in the Je-S form and where appropriate in the Justification of Resources. If several people will be responsible state their roles and responsibilities in the relevant section of the Je-S form. For collaborative projects explain the coordination of data management responsibilities across partners in your Data Management Plan.